Literature for Data Science


Link to the Homepage: Data Science


no image available Bishop, Christopher M
Pattern recognition and machine learning
Springer 2009
  • print: BISh ch 2009:1 1.Ex
no image available Brunton, Steven L. and Kutz, Nathan
Data-driven science and engineering:
Machine learning, dynamical systems, and control
Cambridge 2019
no image available Géron, Aurélien
Hands-on machine learning with Scikit-Learn, Keras, and TensorFlow:
Concepts, tools, and techniques to build intelligent systems
O'Reilly 2019
no image available Goodfellow, Ian
Deep learning
MIT 2016
no image available Hastie, Trevor; Tibshirani, Robert and Friedman, Jerome H.
The elements of statistical learning
Springer 2011
no image available James, Gareth et al.
An introduction to statistical learning:
With applications in R
Springer 2021
no image available Murphy, Kevin P.
Machine learning:
A probabilistic perspective
MIT 2012
no image available Russell, Stuart and Norvig, Peter
Artificial intelligence:
A modern approach
Pearson 2021
no image available Spiegelhalter, David J.
The art of statistics:
Learning from data
Pelican 2019
  • print: SpIE d 2020:1 1.Ex
no image available Sutton, Richard S. and Barto, Andrew
Reinforcement learning:
An introduction
MIT 2018
no image available Wintjen, Marc and Vlahutin, Andrew
Practical data analysis using Jupyter notebook
Packt 2020